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Running on Zero
| title: Next Forcing World Model | |
| emoji: 🎬 | |
| colorFrom: purple | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 6.25.0 | |
| app_file: app.py | |
| short_description: Causal world model for robot video generation | |
| python_version: "3.12" | |
| startup_duration_timeout: 1h | |
| # Next Forcing: Causal World Modeling with Multi-Chunk Prediction | |
| This Space demonstrates **Next Forcing**, a causal autoregressive world model that generates robot manipulation video | |
| from initial camera observations and a text instruction. | |
| ## How it works | |
| 1. Provide top-down and wrist camera images (the initial scene). | |
| 2. Describe the manipulation task in natural language. | |
| 3. The model autoregressively generates future video chunks (4 frames per chunk). | |
| The model is a 5.1B parameter causal video-action transformer (based on the Wan2.1 architecture) that jointly | |
| denoises video latents and action latents in a causal, chunk-by-chunk fashion. | |
| ## Model | |
| - **Checkpoint**: [`gangweix/next-forcing-base`](https://huggingface.co/gangweix/next-forcing-base) (5.1B, BF16) | |
| - **Paper**: [arXiv:2606.11187](https://arxiv.org/abs/2606.11187) | |
| - **Code**: [github.com/gangweix/next-forcing](https://github.com/gangweix/next-forcing) | |
| ## Reference | |
| ``` | |
| @article{xu2026next, | |
| title={Next Forcing: Causal World Modeling with Multi-Chunk Prediction}, | |
| author={Xu, Gangwei and Zhang, Qihang and Zhou, Jiaming and Zhu, Xing and Shen, Yujun and Yang, Xin and Xu, Yinghao}, | |
| journal={arXiv preprint arXiv:2606.11187}, | |
| year={2026} | |
| } | |
| ``` |